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The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genotypes recommendation. Thus, the objectives of this study were: i) propose the Multi-Environment Index Based on Factor Analysis and Ideotype-Design/Markov Chain Monte Carlo (FAI/MCMC index), and ii) apply it for soybean genotypes recommendation. To this end, a data set with 30 soybean genotypes evaluated in 10 environments for grain yield trait was used. Variance components, genetic parameters and genetic values were estimated through MCMC algorithm. Environmental stratification was conducted by factor analyses and the selection of soybean genotypes was performed using the FAI/MCMC index. The results indicated the existence of genotypic variability and G×E interaction. The environments were grouped into three factors. The predicted genetic gains from indirect selection was 4.81%. Thus, our results suggest that the FAI/MCMC index can be successfully used in soybean breeding. Made available in DSpace on 2022-01-21T01:15:57Z (GMT). No. of bitstreams: 1 environmental-stratification-and-genotype.pdf: 544496 bytes, checksum: 092e3a908598522ee76ed714e37068ca (MD5) Previous issue date: 2021

In multi-environment trials (MET), large networks are assessed for results improvement. However, genotype by environment interaction plays an important role in the selection of the most adaptable and stable genotypes in MET framework. In this study, we tested different residual variances and measure the selection gain of cotton genotypes accounting for adaptability and stability, simultaneously. Twelve genotypes of cotton were bred in 10 environments, and fiber length (FL), fiber strength (FS), micronaire (MIC), and fiber yield (FY) were determined. Model selection for different residual variance structures (homogeneous and heterogeneous) was tested using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The variance components were estimated through restricted maximum likelihood and genotypic values were predicted through best linear unbiased prediction. The harmonic mean of relative performance of genetic values (HMRPGV) were applied for simultaneous selection for adaptability, stability, and yield. According to BIC heterogeneous residual variance was the best model fit for FY, whereas homogeneous residual variance was the best model fit for FL, FS, and MIC traits. The selective accuracy was high, indicating reliability of the prediction. The HMRPGV was capable to select for stability, adaptability and yield simultaneously, with remarkable selection gain for each trait. Made available in DSpace on 2022-02-13T01:57:44Z (GMT). No. of bitstreams: 1 MODELS-FOR-OPTIMIZING-SELECTION-BASED-ON-ADAPTABILITY.pdf: 950073 bytes, checksum: 5909b05e3bda8c464287e292d89d14ce (MD5) Previous issue date: 2021

Multiple-trait model tends to be the best alternative for the analysis of repeated measures, since they consider the genetic and residual correlations between measures and improve the selective accuracy. Thus, the objective of this study was to propose a multiple-trait Bayesian model for repeated measures analysis in Jatropha curcas breeding for bioenergy. To this end, the grain yield trait of 730 individuals of 73 half-sib families was evaluated over six harvests. The Markov Chain Monte Carlo algorithm was used to estimate genetic parameters and genetic values. Genetic correlation between pairs of measures were estimated and four selective intensities (27.4%, 20.5%, 13.7%, and 6.9%) were used to compute the selection gains. The full model was selected based on deviance information criterion. Genetic correlations of low (ρg ≤ 0.33), moderate (0.34 ≤ ρg ≤ 0.66), and high magnitude (ρg ≥ 0.67) were observed between pairs of harvests. Bayesian analyses provide robust inference of genetic parameters and genetic values, with high selective accuracies. In summary, the multiple-trait Bayesian model allowed the reliable selection of superior Jatropha curcas progenies. Therefore, we recommend this model to genetic evaluation of Jatropha curcas genotypes, and its generalization, in other perennials.

The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genetic selection. Thus, the present study aimed to estimate genetic parameters and to compare different selection strategies in the context of mixed models for soybean breeding. For this, data referring to the evaluation of 30 genotypes in 10 environments, regarding the grain yield trait, were used. The variance components were estimated through restricted maximum likelihood (REML) and genotypic values were predicted through best linear unbiased prediction (BLUP). Significant effects of genotypes and G×E interaction were detected by the likelihood ratio test (LRT). Low genotypic correlation was obtained across environments, indicating complex G×E interaction. The selective accuracy was very high, indicating high reliability. Our results showed that the most productive soybean genotypes have high adaptability and stability. RESUMO: A interação genótipo × ambiente (G × E) desempenha um papel essencial na expressão fenotípica e pode provocar dificuldades na seleção genética. Assim, o presente estudo teve como objetivo estimar parâmetros genéticos e comparar diferentes estratégias de seleção no contexto de modelos mistos para melhoramento da soja. Para isso, foram utilizados dados referentes à avaliação de 30 genótipos em dez ambientes, referentes à característica produtividade de grãos. Os componentes de variância foram estimados pela máxima verossimilhança restrita (REML) e os valores genotípicos foram preditos pela melhor previsão imparcial linear (BLUP). Efeitos significativos dos genótipos e interação G × E foram detectados pelo teste da razão de verossimilhança (LRT). Correlação genotípica baixa foi obtida entre os ambientes indicando interação G × E do tipo complexa. A acurácia seletiva foi muito alta, indicando alta confiabilidade. Os resultados mostraram que os genótipos de soja mais produtivos apresentam alta adaptabilidade e estabilidade.

An accurate, efficient and informative statistical method for analyses of genotype × environment (G × E) interactions is a key requirement for progress in any breeding program. Thus, the objective of this study was to quantify individual variation in reaction norms using random regression models fitted through Legendre polynomials in eucalyptus (Eucalyptus spp.) breeding. To this end, a data set with 215 eucalyptus clones of different species and hybrids evaluated in four environments for diameter at breast height (DBH) and Pilodyn penetration (PP) was used. Variance components were estimated by restricted maximum likelihood, and genetic values were predicted by best linear unbiased prediction. The best-fitted model for DBH and PP was indicated by the Akaike information criterion, and the significance of the genotype effects was tested using the likelihood ratio test. Genetic variability between eucalyptus clones and very high accuracies ( r^gg >=0.90 ) were detected for both traits. Reaction norms and eigenfunctions generated genetic insights into G × E interactions. This is the first study that quantified individual variation in reaction norms using random regression models fitted through Legendre polynomials in eucalyptus breeding and demonstrated the great potential of this technique. Made available in DSpace on 2021-01-29T00:53:54Z (GMT). No. of bitstreams: 1 Quantifying-individual-variation.pdf: 1478774 bytes, checksum: 4b77df5cb6b88900cdea7d542af2e935 (MD5) Previous issue date: 2020

Most studies on genomic selection in plant breeding compare different statistical methods of univariate approach. However, multi-trait methodologies should be considered since they allow the simultaneous selection of superior genotypes in several economic traits. Here, the aims were to compare the selection accuracy and efficiency of the multivariate partial least square (MPLS) method compared with random regression best linear unbiased predictor (rrBLUP), Bayesian Lasso (Blasso) and univariate partial least square (UPLS) and to develop genomic selection indexes efficient for superior genotypes identification in plant breeding. Ten F2 populations with 800 individuals were simulated, considering four traits with different heritabilities. Genomic selection analyses using rrBLUP, Blasso, UPLS, and MPLS were conducted. Four genomic selection indexes were elaborated by the sum of the marker effects obtained for each trait, weighted by the respective residual variance. Multi-trait indexes were developed based on the assumptions of each methodology mentioned (rrBLUP, Blasso, UPLS, and MPLS), and were denominated I-rrBLUP, I-Blasso, I-UPLS, and I-MPLS. Processing time, selective accuracy, selection gains, and selection coincidence were used to compare the methods and the selection indexes proposed. The MPLS method had similar results compared to UPLS method for the low heritability traits and was less efficient than the rrBLUP and Blasso. The genome selection indexes provided the highest total genetic gains. The I-rrBLUP and I-MPLS indexes stood out for high efficiency in selecting superior genotypes in the shortest processing time. Results suggest that the genomic selection indexes proposed in this study may be promising for plant breeding programs.

As with most sandy beach invertebrates, tiger beetles respond negatively to anthropogenic disturbances. However, impact assessments using these insects have never been conducted on tropical sandy beaches. The aim of the present study was to compare the sensitivity of tiger beetles to human impacts with other macroinvertebrates both locally and globally based on field collections and an extensive literature review. At the local scale, the abundance of Cylindera nivea (Kirby, 1818) was compared in the intertidal zone of six sandy beaches with distinct levels of human disturbances at two periods, in the low and high tourism seasons. The abundance of C. nivea was negatively (p

Despite being a species with great potential for biodiesel production, little research has been done on the breeding of Jatropha curcas, mainly with respect to its yield across harvests. Thus, the present study was carried out to analyze longitudinal data via multiple-trait Best Linear Unbiased Prediction (BLUP) for the genetic improvement of Jatropha curcas. The experiment was set up as a randomized block design with two blocks and five plants per plot. The seed yield of 730 individuals of 73 half-sib families was evaluated over six years. Variance components and genetic parameters were estimated via Restricted Maximum Likelihood (REML). The Additive Index was used for ranking and selection purposes. Genetic correlations of low to moderate magnitude were observed between pairs of harvests. The Multiple-trait BLUP / Additive Index procedure allowed for the selection of superior families based on the predicted genetic values, considering all the harvests. Therefore, it can be efficiently applied in the breeding of Jatropha curcas.

Sandy beaches pollution by marine debris imposes arguably threats for the biodiversity, but interaction of beach bioindicators (e.g., ghost crabs) with debris has been rarely assessed. We aimed to test whether the Atlantic ghost crab Ocypode quadrata (Fabricius, 1787) misidentifies marine debris as food sources. Cigarette butts, straws, popsicle sticks, paper napkins and styrofoams were mixed into solutions with odour of natural and industrialized food. The debris were placed around burrows on beaches with distinct human pressures (low, medium and high-impact). The species interacted with marine debris more frequently in situations of lower human impact, lower prey abundance and larger burrow diameter. These results indicate that in areas with low prey availability and larger individuals, interactions between ghost crabs and debris left by beach visitors and/or transported by winds and currents to low-impact beaches are more likely to occur, mainly near to urbanized areas.

The performance of textile processes and the quality of the products depends on the several cotton (Gossypium hirsutum L.) fiber quality traits, such as micronaire index, fiber length, and fiber strength. This research aims to recommend cotton genotypes for the Brazilian Cerrado based on fiber yield and fiber quality traits. Nineteen cotton cultivar variety trials were performed in the 2013?2014 and 2014?2015 crop seasons. Each trial was conducted as a randomized complete block design with 12 treatments and four replications. The evaluated traits were fiber yield, fiber length, fiber strength, and micronaire. For each trait, a modified Lin and Binns method was used to recommend the best genotypes for all environments (favorable and unfavorable). This method was also used in a multivariate manner, aiming at a general recommendation of genotypes based on the multiple traits evaluated. The genotype ´ environment interaction was significant for all evaluated traits. Genotypes with high adaptability and stability were identified for each trait. The multivariate method identified IMA 08 WS and BRS 335 as the genotypes that had the best combination of main desirable traits. The analysis further revealed that new crosses could be performed between genotypes with high yield adaptability and stability and genotypes with adequate fiber quality traits.

The effects of trampling are usually confounded by the diffuse impacts of the urbanization of sandy beaches. We performed a controlled experiment on a beach with low visitation rates to test the hypothesis that ghost crabs avoid building their burrows on impacted plots as a result of the compacted sediment, and they migrate to non-trampled areas. The sampling design encompassed 11 survey quadrats (6 × 6 m) above the strandline, including five trampled plots (100, 300, 900, 1500 and 3000 steps) and six non-trampled plots. The plots were sampled before and after 24, 48 and 72 h of experimental trampling. We found that the ghost crabs avoided building their burrows in only the 1500× and 3000× trampled plots after 24 h, but the avoidance was not related to sediment compactness. Additionally, the emersion time and escape distance from humans were significantly delayed in the most trampled plots, suggesting a lower surface activity and an avoidance of irregular (i.e. high micro-relief) sediment surfaces by ghost crabs, which might reduce their ability to perceive potential predators.

Intense tourism and human activities have resulted in habitat destruction in sandy beach ecosystems with negative impacts on the associated communities. To investigate whether urbanized beaches affect surf zone fish communities, fish and their benthic macrofaunal prey were collected during periods of low and high human pressure at two beaches on the Southeastern Brazilian coast. A BACI experimental design (Before-After-Control-Impact) was adapted for comparisons of tourism impact on fish community composition and structure in urbanized, intermediate and non-urbanized sectors of each beach. At the end of the summer season, we observed a significant reduction in fish richness, abundance, and diversity in the high tourist pressure areas. The negative association between visitors’ abundance and the macrofaunal density suggests that urbanized beaches are avoided by surf zone fish due to higher human pressure and the reduction of food availability. Our results indicate that surf zone fish should be included in environmental impact studies in sandy beaches, including commercial species, e.g., the bluefish Pomatomus saltatrix . The comparative results from the less urbanized areas suggest that environmental zoning and visitation limits should be used as effective management and preservation strategies on beaches with high conservation potential.

Genetic study in maize (Zea mays) germplasm development is an important step to understand the genetic variability and complementarity between heterotic groups, as well as additive and dominance genetic effects. Thus, diallel analyses have been widely adopted with the aim of identifying the best parental lines and the best crosses. In addition, different environmental conditions make genetic selection difficult. Thus, the objectives of this study were to compare individual and joint analyses of a diallel design through a mixed model methodology for maize breeding, and to evaluate and interpret the genetic effects and their interaction with the environmental effect. Thirteen F2 hybrids were crossed in an incomplete diallel scheme. Seventy-eight inter-population hybrids, and thirteen self-pollinated parents were evaluated. Eleven traits were evaluated, and emphasis was given to the Grain Yield (GY) trait. The significance of the GY trait, specifically, varied across environments. Joint analysis, in particular, presented significance for dominance and additive by environment interaction effects. Joint analysis had the highest selective accuracies for six traits. The correlation coefficients showed similar results, with values from 0.15 to 0.50 between pairs of environments. Gains with selection, considering each environment, ranged from 9.17 to 20.66%, when five hybrids were selected. When direct gains were compared with indirect gains, combined analysis confirmed the high efficiency of selection. For selection of parents, combined analysis achieves the same results as direct selection when two parents were selected.

An efficient and informative statistical method to analyze genotype-by-environment interaction (GxE) is needed in maize breeding programs. Thus, the objective of this study was to compare the effectiveness of multiple-trait models (MTM), random regression models (RRM), and compound symmetry models (CSM) in the analysis of multi-environment trials (MET) in maize breeding. For this, a data set with 84 maize hybrids evaluated across four environments for the trait grain yield (GY) was used. Variance components were estimated by restricted maximum likelihood (REML), and genetic values were predicted by best linear unbiased prediction (BLUP). The best fit MTM, RRM, and CSM were identified by the Akaike information criterion (AIC), and the significance of the genetic effects were tested using the likelihood ratio test (LRT). Genetic gains were predicted considering four selection intensities (5, 10, 15, and 20 hybrids). The selected MTM, RRM, and CSM models fit heterogeneous residuals. Moreover, for RRM the genetic effects were modeled by Legendre polynomials of order two. Genetic variability between maize hybrids were assessed for GY. In general, estimates of broad-sense heritability, selective accuracy, and predicted selection gains were slightly higher when obtained using MTM and RRM. Thus, considering the criterion of parsimony and the possibility of predicting genetic values of hybrids for untested environments, RRM is a preferential approach for analyzing MET in maize breeding.

The genus Cynodon includes species that have huge potential to produce high-quality fodder, for grazing and hay production. In perennial forage breeding, selection should be performed based on repeated measurements in the same individual over time, which maximizes the selective efficiency. Thus, the objectives of this study were to estimate the coefficients of repeatability and optimal number of measures for the genetic selection of Cynodon spp. clones. We evaluated 202 clones, being five checks, during four harvests, in augmented block design. A mixed model methodology (REML/BLUP) was used to estimate the variance components and predict the genotypic values. The repeatability coefficient for plant height, green weight, dry matter, and plant vigor were equal to 0.50, 0.67, 0.25, and 0.73, respectively. The accuracies obtained by performing m repeated measures revealed that 5, 2, 13, and 2 measurements are required to attain an accuracy ≥ 90% in genetic gain from the selection for plant height, green weight, dry matter, and plant vigor, respectively. Furthermore, the efficiency of performing four measurements compared with that of performing only one measurement was 27%, 15%, 51%, and 12% for plant height, green weight, dry matter, and vigor, respectively. In addition, the additive index, adopting a 10% selection intensity, was used in simultaneous selection, leading to desirable genetic gains for plant height, green weight, and plant vigor. In conclusion, the use of the repeatability coefficient suggests performing three measurements to obtain a high accuracy and good efficiency on the selection of superior genotypes of Cynodon spp.

Random regression models (RRM) are a powerful tool to evaluate genotypic plasticity over time. However, to date, RRM remains unexplored for the analysis of repeated measures inJatropha curcasbreeding. Thus, the present work aimed to apply the random regression technique and study its possibilities for the analysis of repeated measures inJatropha curcasbreeding. To this end, the grain yield (GY) trait of 730 individuals of 73 half-sib families was evaluated over six years. Variance components were estimated by restricted maximum likelihood, genetic values were predicted by best linear unbiased prediction and RRM were fitted through Legendre polynomials. The best RRM was selected by Bayesian information criterion. According to the likelihood ratio test, there was genetic variability among theJatropha curcasprogenies; also, the plot and permanent environmental effects were statistically significant. The variance components and heritability estimates increased over time. Non-uniform trajectories were estimated for each progeny throughout the measures, and the area under the trajectories distinguished the progenies with higher performance. High accuracies were found for GY in all harvests, which indicates the high reliability of the results. Moderate to strong genetic correlation was observed across pairs of harvests. The genetic trajectories indicated the existence of genotype × measurement interaction, once the trajectories crossed, which implies a different ranking in each year. Our results suggest that RRM can be efficiently applied for genetic selection inJatropha curcasbreeding programs.

Sandy beaches are ecosystems under increasing human pressure that require efficient management and conservation strategies. Resident macroinvertebrates usually respond to disturbances by changing their behaviour and abundance, and therefore they may be used as indicator species using simple and low-cost monitoring strategies. We synthesize information from the scientific literature on the use of sandy beach macroinvertebrates as indicators of human disturbances operating at local scales. Response ratios were applied to perform a meta-analysis supported by empirical data to objectively assess the magnitude of human disturbances on beach fauna. The “compare and contrast” approach represented some 80% of the studies. Gradient assessments were performed by 16% of the studies, though without determining thresholds of disturbance. Long-term monitoring (encompassing more than two years) was the general approach used in studies about harvesting, but it was not used when assessing other type of disturbances. Causality relationships and mechanisms underlying impacts were rarely assessed. Useful indicators to specific human disturbances were: 1) ghost crabs, which indicate the negative effects of vehicle traffic and nourishment; 2) talitrids as indicators of trampling and mechanical cleaning; and 3) clams as indicators of harvesting. As beaches are affected by multiple stressors acting simultaneously, the relative importance of each one has been difficult to reveal. It remains a priority to identify how different human disturbances are affecting macroinvertebrates under a range of diffuse impacts. Such results would allow for the depiction of patterns and future studies should prioritize gradient analyses and manipulative experiments to provide thresholds of specific stressors and mechanisms of impacts.

Cotton provides about 90% of the world textile fiber, and is one of the crops of greater industrial relevance. The objectives of this study were to estimate the inbreeding depressionand the genetic effects involved in the control of the agronomic andfiber quality traits in F1 and F2 generations and to identify promising hybrids for obtaining superior cotton genotypes. Two cultivars of upland cotton and two moco (Brazilian endemic) cotton were crossed using a half-diallel scheme. The following traits were evaluated: percentage of fibers and weight of one boll, fiber length, fiber uniformity, short fiber index, fiber strength, and micronaire index. The additive genetic effects are predominant in the evaluated agronomic and fiber quality traits. Cultivar FM 966 is the most suitable parent to compose crossing blocks for the improvement of cotton agronomic and fiber quality traits. The hybrids FM 966 × CNPA 7MH and FM 966 × BRS 286 are the most promising for obtaining segregating populations aiming to select superior genotypes. Inbreeding depression is more pronounced in the agronomic traits than in the fiber quality traits.

The genetic diversity of Brazilian Jatropha (Jatropha curcas) germplasm collection (BJGC), which consists of 192 accessions, has been previously reported based on the evaluation of a limited number of RAPD and SSR markers. In addition, accessions from other countries (Guatemala and Mexico) were introduced to this collection without prior information on their relation with the existing collection. Thus the objective of this study were to develop and validate a panel for high-density genome-wide molecular markers for Jatropha; to compare the diversity of the germplasm collected in Brazil and the materials introduced and/or generated by crossing selected genotypes; and to determine whether the germplasm introduction strategies and the controlled crossings were efficient in generating/increasing the genetic variability available to the breeding program. This study reported an evaluation on the existence and on the structure of the genetic diversity of a core collection of 92 accessions by using DArT and SNP markers. The genotyping-by-sequencing approach allowed genotyping 747 polymorphic SNP and 4007 DArTs. The pairwise genetic dissimilarity was estimated according to the Jaccard’s coefficient, and clustered by the UPGMA and Tocher’s clustering methods The genetic diversity distribution was assessed by the analysis of molecular variance (AMOVA). The mean dissimilarity between accessions was low (0.165), and it confirmed that the diversity of the BJGC is very limited. Cluster analysis demonstrated that the introduced genotypes were divergent, and they formed a separate group, indicating that new introductions such as these will be important to promote future efforts on genetic breeding. Accordingly, data from SNP also confirmed the development of a significant amount of genetic variability within families (65%), which probably resulted from the use of the Mexican accession that was found to be considerably divergent when compared with the Brazilian accessions. These results indicate that breeders should focus on two main strategies to generate variability in the BJGC: introduction of new accessions from other countries and crossings between potential genotypes.

The objective of this work was to estimate the predicted genetic gains with the simultaneous selection of agronomic and technological traits from elite cotton lines using selection indexes. Data from the evaluation of 36 elite lines were evaluated in three trials located in Apodi-RN in 2013 and 2014 and Santa Helena, GO, Brazil in 2013, in a randomized block design with two replicates. The agronomic traits evaluated were: plant height (PH), average boll weight (ABW), percentage of fibers (PF) and seed cotton yield (YIE). In 20 bolls from each experimental unit, the following technological fiber traits were evaluated: fiber length (UHM), fiber uniformity (UNIF), short fiber index (SFI), fiber strength (FS), elongation (ELON), micronaire (MIC), reflectance (RD) and degree of yellowing (+b). Smith and Hazel, Pesek and Baker and Mulamba and Mock selection indexes were tested for selection of the seven superior genotypes, assigning the coefficients of genetic variation (CVg) as economic weight. There were no interaction between genotypes and environments for any of the evaluated traits. Smith and Hazel index resulted in negative gains for fiber length and positive for the traits whose reduction is of interest, such as plant height, micronaire and degree of yellowing. Pesek and Baker index provided positive predictive gains for all traits of interest. However, it promoted reduction only to the degree of yellowing. Mulamba and Mock presented satisfactory gains, being the most suitable for selecting genotypes aiming at simultaneous gains in yield and fiber technological components.

This study aimed to estimate the genetic diversity among soursop genotypes in terms of fruit yield evaluated in different crop years. Sixteen measurements for fruit yield in 71 soursop genotypes were carried out from 2000 to 2016. Based on ANOVA it was verified the existence of genetic variability among genotypes in the different measurements (harvests). The genotypes were clustered according to their respective fruit yield averages in the 16 years as well as from their means obtained in each measurement year by the Scott-Knott test (p

The increasing anthropogenic disturbance on coastal ecosystems has threatened ecological interactions and ecosystems functioning. To investigate if human pressure affects the trophic structure of sandy beaches, mass-balanced models were applied on two Brazilian sandy beaches with distinct human impact degree. The food web models included detritus, phytoplankton, macroinvertebrates, fish and seabirds. Macroinvertebrates in non-urbanized sectors represented the highest production fraction consumed by predators. The energy transfer and the cycling indicator were more efficient in the non-urbanized sectors than urbanized ones. The results indicate that macroinvertebrates sensitive to direct human impact such as trampling are important to the trophic functioning of sandy beaches. Establishing a threshold for the number of beachgoers or dispersing recreational activities to avoid crowds may be tangible ways to mitigate the trampling impact on macroinvertebrates.

The most conspicuous characteristic of ghost crabs (Crustacea: Ocypodidae) is the construction of semi-permanent burrows on the sand, widely used as tools for impact assessments. Thus, it is now critical to understand the factors driving burrowing activity and burrow occupation rates, including the effects of natural and anthropogenic disturbances. We tested three hypotheses in the present study with the ghost crab Ocypode quadrata: (i) overestimation of population size by traditional burrow counts depends on disturbance level at local scale; (ii) burrow occupation rate is density-dependent; and (iii) the predominant spatial distribution of burrows within the habitat is uniform. The last two predictions were assessed using a meta-analysis for a macro scale assessment. The comparison of distinct methods for burrow counting confirmed that ghost crab density is overestimated on non-urbanized beaches at local scale. A non-linear relationship between burrow occupation rates and burrow density was found at local and regional scales. When burrow density increases, the burrow occupation rate is also higher. However, from approximately 20 to 30 burrows/100 m2, the occupation rate reduces with increased density. Thus, the overestimation of the ghost crab density on non-urbanized beaches can be partially explained by a density-dependence in burrowing activity probably driven by a stronger intraspecific competition on non-urbanized areas. Finally, the distribution pattern of the ghost crab is predominantly uniform in most of its distribution range, despite of urbanization level and sampling design, hence suggesting intra-specific interactions as a driver of burrowing behaviour. In conclusion, burrow density, occupation rate and spatial distribution within the habitat evidenced at various spatial scales that burrowing activity of the ghost crab is density-dependent and this constitutes an issue never considered before in impact assessments inherent to coastal monitoring and management.

Changes in species' abundance have been used as indicators of environmental and anthropogenic disturbances. However, sublethal, e.g., diet, changes should be detected before some alterations in the composition and structure of fish assemblages occur as a result of ecological negative impacts. The objective of the present study was to assess possible changes in surf zone fish diet in response to environmental and anthropogenic disturbances. Surf zone fish were sampled and their stomach contents were analyzed on two sandy beaches under different levels of human pressure in Southeastern Brazil. Habitat variables related to seasonality, food availability, anthropogenic disturbance, upwelling and river influence were measured as follows: (1) wave height; (2) water temperature; (3) intertidal macroinvertebrates abundance; (4) solid waste amount; (5) salinity; (6) particulate organic carbon (POC) and (7) chlorophyll a (Chl a). Our results showed the influence of seasonality, prey abundance and hydrodynamics in prey selection, and diet overlap between typical surf zone residents. A literature search was also performed and it shows that insects and Emerita brasiliensis eggs, which were the main food item consumed by some surf zone fish at urbanized Brazilian beaches, are unusual worldwide. Furthermore, solid waste was related to high consumption of insects by pompanos fish in urbanized areas, suggesting that this fish diet could be a sublethal indicator of human impact on sandy beaches.

Sugarcane is one of the crops of greatest interest in the search for efficient biomass for the production of bioenergy. In addition to the production of sugar and ethanol from sugarcane juice, the industrialization process obtains the biomass, a lignocellulosic material with high energy content, which can be converted into biofuels. Recognized this importance, the objective of this study was to indicate crosses between potential sugarcane genotypes, aiming at the production of sugar and ethanol, and at the use of biomass for the production of bioelectricity or cellulosic ethanol. Ninety sugarcane genotypes of the Active Germplasm Bank of the Federal University of Vicosa were evaluated for 15 chemical and technological variables that characterize the juice and the bagasse. Crosses were defined by the genotypes which presented the best means using the simultaneous selection index, excluding the crosses between the most similar genotypes based on genetic dissimilarity verified by the analyses of diversity. Thus, it was possible to indicate 40 crosses between potential parents with high quality for production of sugar and ethanol and with efficient biomass for production of bioenergy, 19 crosses being for production of bioelectricity, 15 for production of cellulosic ethanol, and 6 for both purposes.

Rbio is a free software for data processing. It is compatible and integrated with the free R software, which is globally accepted for statistical analysis. Thus, Rbio takes advantage of all processing potential of the R software. However, this new software allows the user to perform all the analyses without knowing the programming in R language. Rbio is available in Portuguese; it can be downloaded from the Internet (http://www.biometria.ufv.br), and requires the Windows operating system. It has a set of sample files, making it easy to be used. Currently, it supplies the user with all scripts internally used to process the analyses. Rbio can perform descriptive statistics, analysis of variance, estimation of genetic parameters and means tests, multivariate analysis, nonparametric tests, regressions, correlations, biometrics, bioinformatics, and simulation.

Seabirds collect debris primarily nearby breeding sites, and thus they may be used to monitor these pollutants in the ocean. This study aimed to investigate the prevalence of marine debris used as nesting materials by the brown booby (Sula leucogaster) and to test the species selectivity to debris type and color in two coastal islands of Brazil. We found marine debris in 61% of the brown booby nests on both islands. Fishing gear and hard plastic were the most frequent types of debris. Higher prevalence of fishing gear was found on the island with greater fishery activity. Similarly, hard plastic was the most frequent type of debris in nests and adjacent beach environment. The frequency of debris in brown booby nests can be a potential indicator of the abundance of specific items in surrounding marine waters. Monitoring debris in brown booby nests in a long-term may provide a better understanding of the species⿿ selectivity for specific debris. Furthermore, the impacts of debris in seabird nests at population level remain an overlooked threat that may reduce the quality of nesting habitats. We showed that brown booby nests are widely impacted by marine debris and that these organisms are exposed to this form of pollution from the beginning of their life.

The role of morphodynamic features such as grain size, swash climate and wave action on the macrofauna of beaches are well-known. However, few studies have investigated natural disturbances as potential drivers of temporal community variations. In southeastern Brazil, we sampled the intertidal macrofauna of two sandy beaches to test whether seasonal disturbances as the frequency of storm wave events (SWE) and rainfall have significant influence on their composition and abundance. The macrofauna assemblage differed significantly between the rainy and the dry seasons, but rainfall was not the main driver of community changes, although both beaches are in the vicinity of extensive river plumes. Actually, SWE explained most macrofauna richness overtime, with positive effects. Our results point to the importance of learning more about the effects of poorly studied disturbances on macrofaunal communities, and based on them we strongly recommend including these seasonal phenomena when monitoring sandy beaches.

The objective of the present study was to test whether the Atlantic ghost crab Ocypode quadrata is a reliable biomonitor of microplastic (MP) pollution of beach sediments. To test the hypothesis (H1) that the sediment is the main source of MP ingestion, the proportion of MP types (hard plastic, microfibers, pellet, soft plastic, and extruded polystyrene foam) in the gut content was compared with that on the strandline. The types of MPs in the gut content and sediment had similar proportions; black (~49%) and blue (~45%) microfibers were responsible for this similarity (55%), hence confirming H1. However, the second hypothesis (H2) that prevalence of MP in the gut content is related to its density on beach with distinct urbanization degree was not accepted. These results indicate that high trophic plasticity of the ghost crab and, consequently, multiple-sources of contamination may interfere with its use as a biomonitor of MP pollution.

Pitfalls can trap mobile fauna during their peak surface activity, whereas sediment corer efficiently capture individuals buried in the substrate. Corer sampling is the most used method to capture the sandhopper Atlantorchestoidea brasiliensis, because of the assumption that bias related to surface activity during daylight can be controlled by a careful sampling. The objective of the present study was to evaluate the efficiency of pitfalls to sample the sandhopper A. brasiliensis on sandy beaches with distinct impact levels. We compared our results with a previous impact assessment on the same beach arc that used corer sampling. The sandhopper abundance was more than 10 times higher in the pitfalls compared to the corer samples, suggesting prevalent activity on the sediment surface during daylight and possible bias when using corer sampling to estimate population size. The conclusion of the previous impact assessment, however, was not strongly affected by sampling tools, because seasonal trampling seems to be negative for the number of buried and surface-active individuals. Our results showed that the choice of sampling tool is an important issue to be considered when using sandhoppers as indicator species on sandy beaches.

The aim of the present study was to investigate macroinvertebrates from sandy beaches according to their umbrella potential worldwide. A meta-analysis was performed on a global scale, including 13 marine ecoregions. Community richness and species-specific density of 235 beaches and 726 surveys were retrieved from 48 articles. An index (UI) to select umbrella species was applied according to three categories: percentage of co-occurring species (PCS), median rarity (RAR) and sensitivity to human impacts (DS), which was based on a common statistic representing the magnitude of disturbances in meta-analysis (response ratios). PCS, RAR and DS of the umbrella species were compared with the median ± 95% confidence intervals calculated for all other non-umbrella species. Umbrella potential was higher for species co-occurring in different beach types. Most umbrella taxa responded negatively to human disturbances. These taxa also showed higher percentage of co-occurring species than the mean value (±95% confidence intervals) of non-umbrella species. Macroinvertebrates were ecological indicators of human disturbances and umbrella species, suggesting a good cost-benefit relationship for their application in beach monitoring. The baseline provided in the present study on applying the concept of umbrella species on sandy beaches supports the usefulness of these species in the restoration of urban beaches, monitoring of beaches with social-ecological conflicts and their full protection into reserves.

Forest breeding is a science that has been developing in Brazil since 1941 being the Eucalyptus a highlighted genus in this scenario. In a global scene, Brazil is displayed prominently in productivity of Eucalyptus planting, due to favorable environmental conditions to cultivation development, and the incentive in research for improvement of traits of interest t observed in it species and hybrids. This research included a historical review of Eucalyptus breeding over the years under genetic biometric perspective in Brazil, from reports describing the pioneer planting up to the current genome wide selection (GWS) that came as a complement of forest breeding success. This review showed some of the tracks performed by researchers aiming to improve the productive and quality of phenotypic traits from Eucalyptus genus. RESUMO: O melhoramento florestal é uma ciência que tem tido desenvolvimento no Brasil desde o ano de 1941 e um gênero que obteve grande repercussão neste cenário foi o Eucalyptus . O Brasil apresenta-se em destaque no panorama mundial quanto à produtividade dos plantios de eucalipto, em virtude das condições ambientais favoráveis ao desenvolvimento da cultura e ao incentivo em pesquisas destinadas às melhorias dos caracteres de interesse, presentes em suas espécies e híbridos. Este trabalho inclui uma revisão histórica do melhoramento do eucalipto ao longo dos anos no Brasil, sob a ótica da genética biométrica, desde o relato que descreve o plantio pioneiro de suas espécies no país, até a atual aplicação de seleção genômica ampla (SGA), que surgiu como um complemento de sucesso no melhoramento florestal. A pesquisa ilustra ainda alguns dos caminhos percorridos por pesquisadores a fim de aumentar a produtividade e a qualidade dos caracteres fenotípicos do gênero Eucalyptus.

The objectives of this study were to verify the existence of genetic variability among half-sib families and select the best families in order to increase oil content and reduce toxicity in jatropha seeds. The experiment was carried out in complete randomized block design with two replications and five plants per plot, during five crop years (2010–2014). Plots were evaluated for grain yield (g/plant) and for weight of 100 seeds (g), and in the year of 2014, seed oil content and phorbol ester concentration (mg/g) were also evaluated. Analysis of variance was carried out considering genotypes as random, and from this analysis, genetic parameters were estimated for the characteristics of interest. Diversity analysis was carried out using the Mahalanobis distance matrix. Tocher and UPGMA clustering methods were also used. Gain with selection was estimated using the method of direct selection on the main variable and indirect selection on the other variables, based on the selection of the former. Different selection indexes wegain) in order to estimate the gain and select the top 20 families. The mulre also used (classic, base index, sum of ranks, multiplicative index and index based on the desired tiplicative index was the best index for jatropha because using this index we obtained gain for all traits together. It was concluded that there is genetic variability among half-sib families, and that selected families by multiplicative index made it possible to increase oil content and decrease toxicity in jatropha seeds.

Ghost crabs are exposed to vehicles on sandy beaches and adjacent habitats. The occurrence of individuals on coastal roads constitutes one issue to be considered for beach management at regional scales. In this context, we aimed to test whether the abundance of the ghost crab Ocypode quadrata in the road crossing a beach vegetation is predicted by light intensity. Ghost crabs on the dirt road were searched at night along a beachfront in a vehicle at ∼ 20 km/h. The number of crabs on nearby beaches was counted by walking along the intertidal zone. The probability of finding crabs was lower in moderate-impacted road stretches irrespective of light intensity. The same spatial trends of ghost crabs abundance on the road was found on the beaches at night. Therefore, the population size on the beach may determine the amount of individuals crossing the road and exposed to vehicle collision.

Usually, genetic selection is carried out based on several traits, which can be genetically correlated. In this case, selection bias may occur if these traits are analyzed individually. Thus, the present work aimed to evaluate the applicability and efficiency of multiple-trait best linear unbiased prediction (BLUP) in the genetic selection of Eucalyptus. The data used in this work refer to the evaluation of a partial diallel of Eucalyptus spp. in relation to height, diameter at breast height (DBH), and volume. Variance components and genetic and non-genetic parameters were estimated via residual maximum likelihood (REML). Multiple-trait BLUP led to estimates of mean additive genetic variance higher than the estimates obtained via single-trait BLUP and, consequently, led to higher estimates of narrow-sense individual interpopulational heritabilities and mean accuracies. Partial genetic correlations obtained via multiple-trait BLUP allowed a real understanding of the association between traits, differently from those obtained via single-trait BLUP. Multiple-trait BLUP led to higher gains predicted with the selection for height, DBH, and volume and can be efficiently applied in the genetic selection of Eucalyptus.

Despite its numerous important traits for biodiesel production, little research exists on the Jatropha curcas crop, mainly with respect to repeated measures over time (crop years). The present study was thus developed to evaluate repeated measures over time in Jatropha curcas and examine the applicability and efficiency of the harmonic mean of the relative performance of genetic values (HMRPGV) method in the selection of families for yield, stability, and adaptability, simultaneously. The work involved data from the evaluation of 730 individuals of 73 half-sib families, in a complete randomized block design, during six crop years, for the trait grain yield. Restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) procedure was performed to estimate the variance components and predict the genetic values. Ten crop years must be evaluated to obtain 80% of the maximum coefficient of determination and 90% accuracy in terms of genetic gain from selection. The efficiency of performing 10 measurements compared with the situation in which only one measurement is used was 67%. The HMRPGV method has great potential in the selection of Jatropha curcas families for yield, stability, and adaptability, simultaneously.

Photosynthetic efficiency has become the target of several breeding programs since the positive correlation between photosynthetic rate and yield in soybean suggests that the improvement of photosynthetic efficiency may be a promising target for new yield gains. However, studies on combining ability of soybean genotypes for physiological traits are still scarce in the literature. The objective of this study was to estimate the combining ability of soybean genotypes based on F2 generation aiming to identify superior parents and segregating populations for physiological traits. Twenty-eight F2 populations resulting from partial diallel crossings between eleven lines were evaluated in two crop seasons for the physiological traits: photosynthesis, stomatal conductance, internal CO2 concentration, and transpiration. General combining ability (GCA) of the parents and specific combining ability (SCA) of the F2 populations were estimated. Our findings reveal the predominance of additive effects in controlling the traits. The genotype TMG 7062 IPRO is the most promising parent for programs aiming at photosynthetic efficiency. We have also identified other promising parents and proposed cross-breeding with higher potential for obtaining superior lines for photosynthetic efficiency.

Sandy beaches are sites of marine debris stranding, but the interaction of beach biota with waste is poorly studied. The objective of this study was to investigate whether the ghost crab Ocypode quadrata selects marine debris by types using a non-destructive method on sandy beaches of Southeastern Brazil. We found marine debris in 7% of 1696 surveyed burrows, and the ghost crabs selectivity was mainly by soft plastic (30%), straw (11%), rope (6%) and foam (4%). Burrows with marine debris showed higher occupation rate (~68%) compared to burrows without debris (~28%), indicating that these materials may increase the capacity of ghost crabs to memorize their burrows placement (homing). The percentage of marine debris was not always related to their amount in the drift line, but ghost crabs used more debris near urbanized areas. Future studies should test whether ghost crabs are using marine debris for feeding, homing or other mechanisms.

Jatropha (Jatropha curcas) has become one of the most important species for producing biofuels. Currently, Genotype x Environment (GxE) interaction is the biggest challenge that breeders should solve to increase the section accuracy in the plant breeding. Therefore, the objectives in this study were to estimate the parameters in the 180 half-sib families in Jatropha evaluated for five production years, to verify the significance of the GxE interaction variance, to evaluate the adaptability and stability for each family based on three prediction methods, to select superior half-sib families based on the adaptability and stability analyses, and to predict the accuracy for the sixth production year. Jatropha half-sib families were classified and selected using the follow adaptability and stability methods: linear regression, bi-segmented linear regression and mixed models concepts called harmonic mean of the relative performance of genetic values (HMRPGV). The prediction accuracy was estimated by the Pearson correlation between the predicted genetic values by adaptability and stability methods and the phenotypic value in the sixth production year. In result, most half-sib families were classified as general adaptability and general stability for the evaluated traits. The selection gain obtained via HMRPGV was higher than other methods. The prediction accuracy for the sixth production year was 0.45. Therefore, HMRPGV is efficient to maximize the genetic gain, and it can be a useful strategy to select genotype with high adaptability and stability in Jatropha breeding as well as other species that should be evaluated for many years to take a suitable selection accuracy.

Asian soybean rust (Phakopsora pachyrhizi – ASR) is one of the major diseases that occur in soybean and causes great damage to commercial crops. Therefore, the goal of this work was to investigate the relationship between biochemical and photosyntetic parameters in soybean with ASR. Two experiments were performed in a randomized complete block with three treatments (water, Tween 20, and methyl jasmonate). The evaluated traits were: severity, chlorophyll pools, concentration of phenolic compounds content, enzyme activity, and photosyntetic parameters. Based on Pearson correlation, correlation network and path analysis it was verified that the severity had high correlation with almost all traits evaluated meanwhile photosynthesis is weakly related with almost all traits. Therefore, the occurrence of ASR affects directly the traits related to enzymatic activity and phenolic compounds content in soybean plants inoculated with ASR. The management of ASR is important to keep in normal levels the rates of photosynthesis carried out by the plant, and thus not affect the yield. Besides that, understanding the biochemical mechanisms and ecophysiological responses that occur during the soybean-P. pachyrhizi interaction has a great importance for breeding programs, as it will help for obtaining resistant cultivars or efficient methods in fungus control.

O artigo não contém resumo em português The objectives of this study were to estimate the general and specific combining ability of the parents, and to verify the existence of maternal effect and inbreeding depression in Jatropha. The experiment was carried out from 2010 to 2015, in the municipality of Planaltina, Distrito Federal. The following traits were evaluated: plant height, stem diameter, canopy projection between the row, canopy projection on the row, number of branches, mass of one hundred grains, and grain yield. Cytoplasmic effects and effects of female parent nuclear genes were observed for all traits. Dominance effects were predominant in the genetic control of all traits. Genotypes 107 and 190 were the superior parents for the reduction of the size, and for the increase of grain yield. No inbreeding depression was observed for grain yield. The most promising crosses for the conduction of segregating populations and increment in grain yield were 190x107, 107x190 and 259x107.

Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of soursop (Annona muricata L.) genotypes based on fruit yield. Sixteen measurements of fruit yield from 71 soursop genotypes were carried out between 2000 and 2016. In order to estimate r with the best accuracy, four procedures were used: analysis of variance, principal component analysis based on the correlation matrix, principal component analysis based on the phenotypic variance and covariance matrix, and structural analysis based on the correlation matrix. The minimum number of measurements needed to predict the actual value of individuals was estimated. Principal component analysis using the phenotypic variance and covariance matrix provided the most accurate estimates of both r and the number of measurements required for accurate evaluation of fruit yield in soursop. Our results indicate that selection of soursop genotypes with high fruit yield can be performed based on the third and fourth measurements in the early years and/or based on the eighth and ninth measurements at more advanced stages.

Tetranychus urticae Koch (Acari: Tetranychidae) is considered the main pest of strawberry. Several factors can favor its development, among them the genotype susceptibility and cropping system. The aims of this study were to evaluate the agronomic performance of strawberry cultivars under different managements and to identify strawberry cultivars that meet tolerance to T. urticae and high fruit yield. Thirteen cultivars of strawberry ('Albion', 'Aleluia', 'Aromas', 'Camarosa', 'Camino Real', 'Campinas', 'Diamante', 'Dover', 'Festival', 'Seascape', 'Toyonoka', 'Tudla', and 'Ventana') under three managements (open field, low tunnel, and high tunnel) were evaluated. The T. urticae attack to different cultivars was influenced by managements, being low tunnel the one that provided higher infestations in the most evaluated cultivars. 'Camarosa' was the cultivar with the lower incidence of pest and 'Dover' had the higher infestation. The genotype most suitable for growing under different managements is the 'Festival' genotype, since it meets tolerance to T. urticae, high fruit yield, and phenotypic stability.

Não encontrei o número de páginas. Sugarcane breeding programs have been adapting to a new market demand: aside from high sucrose yield per hectare, the sector needs new cultivars with higher fiber percentages. The selection of sugarcane clones based on phenotype alone is a complex task. The selected clones should display high performance in a series of yield- and quality-related traits. Selection indices can provide information about which clones can best combine the traits of agronomic interest. In this study, different selection indices were evaluated in a population of 220 clones. The following traits were evaluated: weight of 10 stalks with straw, weight of 10 stalks with no straw, tons of cane per hectare with straw, tons of cane per hectare with no straw, sucrose content, fiber percentage, and tons of fiber per hectare. The selection indices of Smith (1936) and Hazel (1943) and Mulamba and Mock (1978), the base index (Williams, 1962), and the index of Pesek and Baker (1969) were used. The selection index of Mulamba and Mock (1978) without economic weight estimates, the index of Mulamba and Mock with economic weights based on heritability, and the index of Pesek and Baker (1969) with the desired gains based on genetic standard deviations were efficient for the selection of energy cane clones with good fiber yield, sucrose content, and tons of cane per hectare.

The effect of urbanization on the environmental quality of two sandy beaches was evaluated using metrics such as pH, dissolved oxygen, coliforms and solid waste. Urbanization effects on physicochemical metrics (pH and dissolved oxygen) were not significant. The coliforms concentration was below the established limit for primary contact, but it was significantly higher on beaches with highest recreational potential. Similarly, the abundance of solid waste was significantly higher in urbanized areas (~4.5 items/m2), and it was higher than what was found for 106 beaches worldwide. Plastic represented 84% of the total number of items and recreational activities were the main sources of debris (80%). Therefore, a balance between recreation and conservation actions, based on short-term (e.g. fines) and long-term measures (e.g. educational policies) is recommended. We demonstrate that the use of multiple metrics provides more robust estimates of the environmental quality of sandy beaches than a single impact metric.

To identify genomic regions involved in the regulation of fundamental physiological processes such as photosynthesis and respiration, a population of Solanum pennellii introgression lines was analyzed. We determined phenotypes for physiological, metabolic, and growth related traits, including gas exchange and chlorophyll fluorescence parameters. Data analysis allowed the identification of 208 physiological and metabolic quantitative trait loci with 33 of these being associated to smaller intervals of the genomic regions, termed BINs. Eight BINs were identified that were associated with higher assimilation rates than the recurrent parent M82. Two and 10 genomic regions were related to shoot and root dry matter accumulation, respectively. Nine genomic regions were associated with starch levels, whereas 12 BINs were associated with the levels of other metabolites. Additionally, a comprehensive and detailed annotation of the genomic regions spanning these quantitative trait loci allowed us to identify 87 candidate genes that putatively control the investigated traits. We confirmed 8 of these at the level of variance in gene expression. Taken together, our results allowed the identification of candidate genes that most likely regulate photosynthesis, primary metabolism, and plant growth and as such provide new avenues for crop improvement. Instituto de Biotecnología Fil: Oliveira Silva, Franklin Magnum de. Universidade Federal de Viçosa. Departamento de Biologia Vegetal. Max‐Planck Partner Group; Brasil Fil: Lichtenstein, Gabriel. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina Fil: Lichtenstein, Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Alseekh, Saleh. Max Planck Institute of Molecular Plant Physiology. Department of Molecular Physiology; Alemania Fil: Rosado‐Souza, Laise. Max Planck Institute of Molecular Plant Physiology; Alemania Fil: Conte, Mariana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina Fil: Conte, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Fuentes Suguiyama, Vanessa. Universidade Federal do ABC; Brasil Fil: Lira, Bruno Silvestre. Universidade de São Pablo. Instituto de Biociencias. Departamento de Botânica; Brasil Fil: Fanourakis, Dimitrios. Department of Viticulture, Floriculture, Vegetable Crops and Plant Protection; Grecia Fil: Usadel, Björn. Rheinisch-Westfälische Technische Hochschule Aachen University. Institute for Botany and Molecular Genetics (IBMG). Institute for Biology I; Alemania Fil: Usadel, Björn. Forschungszentrum Jülich. Institut für Bio- und Geowissenschaften 2 (IBG-2); Alemania Fil: Lopes Bhering, Leonardo. Universidade Federal de Viçosa. Departamento de Biologia Geral; Brasil Fil: DaMatta, Fábio M. Universidade Federal de Viçosa. Departamento de Biologia Vegetal; Brasil Fil: Sulpice, Ronan. National University of Ireland Galway. Plant & Agribiosiences. Plant and AgriBiosciences Research Centre. Plant Systems Biology Lab; Irlanda Fil: Araújo, Wagner L. Universidade Federal de Viçosa. Departamento de Biologia Vegetal. Max‐Planck Partner Group; Brasil Fil: Rossi, Magdalena. Universidade de São Pablo. Instituto de Biociencias. Departamento de Botânica; Brasil Fil: de Setta, Nathalia. Universidade Federal do ABC; Brasil Fil: Fernie, Alisdair R. Max Planck Institute of Molecular Plant Physiology. Department of Molecular Physiology; Alemania Fil: Carrari, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina Fil: Carrari, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina Fil: Nunes Nesi, Adriano. Universidade Federal de Viçosa. Departamento de Biologia Vegetal. Max‐Planck Partner Group; Brasil

Cotton produces one of the most important textile fibers of the world and has great relevance in the world economy. It is an economically important crop in Brazil, which is the world's fifth largest producer. However, studies evaluating the genotype x environment (G x E) interactions in cotton are scarce in this country. Therefore, the goal of this study was to evaluate the G x E interactions in two important traits in cotton (fiber yield and fiber length) using the method proposed by Eberhart and Russell (simple linear regression) and reaction norm models (random regression). Eight trials with sixteen upland cotton genotypes, conducted in a randomized block design, were used. It was possible to identify a genotype with wide adaptability and stability for both traits. Reaction norm models have excellent theoretical and practical properties and led to more informative and accurate results than the method proposed by Eberhart and Russell and should, therefore, be preferred. Curves of genotypic values as a function of the environmental gradient, which predict the behavior of the genotypes along the environmental gradient, were generated. These curves make possible the recommendation to untested environmental levels.

Jatropha is a species with great potential for biodiesel production, and the knowledge on how the main agronomic traits are correlated will contribute to its improvement. Therefore, the objectives of this study were to estimate the genetic parameters of the traits: plant height at 12 and 40 months, canopy projection on the row at 12 and 40 months, canopy projection between the row at 12 and 40 months, number of branches at 40 months, grain yield, and oil yield; to verify the existence of phenotypic correlation between these traits; to verify the influence of the morphological traits on oil yield by means of path analysis; and to evaluate the relationship between the productive traits in Jatropha and the morphological traits measured at different ages. Sixty-seven half-sib families were evaluated using a completely randomized block design with two replications and five plants per plot. Analysis of variance was used to estimate the genetic value. Phenotypic correlations were given by the Pearson correlation between traits. For the canonical correlation analysis, two groups of traits were established: group I, consisting of traits of economic importance for the culture, and group II, consisting of morphological traits. Path analysis was carried out considering oil yield as the main dependent variable. Genetic variability was observed among Jatropha families. Productive traits can be indirectly selected via morphological traits due to the correlation between these two groups of traits. Therefore, canonical correlations and path analysis are two strategies that may be useful in Jatropha-breeding program when the objective is to select productive traits via morphological traits.